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  • 1
    Godot RL Agents

    Godot RL Agents

    An Open Source package that allows video game creators

    godot_rl_agents is a reinforcement learning integration for the Godot game engine. It allows AI agents to learn how to interact with and play Godot-based games using RL algorithms. The toolkit bridges Godot with Python-based RL libraries like Stable-Baselines3, making it possible to create complex and visually rich RL environments natively in Godot.
    Downloads: 2 This Week
    Last Update:
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  • 2
    Habitat-Lab

    Habitat-Lab

    A modular high-level library to train embodied AI agents

    Habitat-Lab is a modular high-level library for end-to-end development in embodied AI. It is designed to train agents to perform a wide variety of embodied AI tasks in indoor environments, as well as develop agents that can interact with humans in performing these tasks. Allowing users to train agents in a wide variety of single and multi-agent tasks (e.g. navigation, rearrangement, instruction following, question answering, human following), as well as define novel tasks. ...
    Downloads: 6 This Week
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  • 3
    Multi-Agent Orchestrator

    Multi-Agent Orchestrator

    Flexible and powerful framework for managing multiple AI agents

    Multi-Agent Orchestrator is an AI coordination framework that enables multiple intelligent agents to work together to complete complex, multi-step workflows.
    Downloads: 4 This Week
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  • 4
    AgentUniverse

    AgentUniverse

    agentUniverse is a LLM multi-agent framework

    AgentUniverse is a multi-agent AI framework that enables coordination between multiple intelligent agents for complex task execution and automation.
    Downloads: 9 This Week
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  • 5
    TaskWeaver

    TaskWeaver

    A code-first agent framework for seamlessly planning analytics tasks

    TaskWeaver is a multi-agent AI framework designed for orchestrating autonomous agents that collaborate to complete complex tasks.
    Downloads: 2 This Week
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  • 6
    TensorHouse

    TensorHouse

    A collection of reference Jupyter notebooks and demo AI/ML application

    TensorHouse is a scalable reinforcement learning (RL) platform that focuses on high-throughput experience generation and distributed training. It is designed to efficiently train agents across multiple environments and compute resources. TensorHouse enables flexible experiment management, making it suitable for large-scale RL experiments in both research and applied settings.
    Downloads: 7 This Week
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  • 7
    TradeMaster

    TradeMaster

    TradeMaster is an open-source platform for quantitative trading

    TradeMaster is a first-of-its-kind, best-in-class open-source platform for quantitative trading (QT) empowered by reinforcement learning (RL), which covers the full pipeline for the design, implementation, evaluation and deployment of RL-based algorithms. TradeMaster is composed of 6 key modules: 1) multi-modality market data of different financial assets at multiple granularities; 2) whole data preprocessing pipeline; 3) a series of high-fidelity data-driven market simulators for mainstream...
    Downloads: 2 This Week
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  • 8
    Gym

    Gym

    Toolkit for developing and comparing reinforcement learning algorithms

    Gym by OpenAI is a toolkit for developing and comparing reinforcement learning algorithms. It supports teaching agents, everything from walking to playing games like Pong or Pinball. Open source interface to reinforce learning tasks. The gym library provides an easy-to-use suite of reinforcement learning tasks. Gym provides the environment, you provide the algorithm. You can write your agent using your existing numerical computation library, such as TensorFlow or Theano.
    Downloads: 7 This Week
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  • 9
    RL Baselines Zoo

    RL Baselines Zoo

    A collection of 100+ pre-trained RL agents using Stable Baselines

    RL Baselines Zoo is a comprehensive training framework and collection of pre-trained RL agents using Stable-Baselines3. It offers tools for training, tuning, and evaluating RL algorithms across many standard environments, including MuJoCo, Atari, and robotics simulations. Designed for reproducible RL research and benchmarking, it includes scripts, hyperparameter presets, and best practices for training robust agents.
    Downloads: 0 This Week
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  • 10
    ChainerRL

    ChainerRL

    ChainerRL is a deep reinforcement learning library

    ...PFRL is the PyTorch analog of ChainerRL. ChainerRL has a set of accompanying visualization tools in order to aid developers' ability to understand and debug their RL agents. With this visualization tool, the behavior of ChainerRL agents can be easily inspected from a browser UI. Environments that support the subset of OpenAI Gym's interface (reset and step methods) can be used.
    Downloads: 0 This Week
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  • 11
    Spinning Up in Deep RL

    Spinning Up in Deep RL

    Educational resource to help anyone learn deep reinforcement learning

    ...This is an educational resource produced by OpenAI that makes it easier to learn about deep reinforcement learning (deep RL). For the unfamiliar, reinforcement learning (RL) is a machine learning approach for teaching agents how to solve tasks by trial and error. Deep RL refers to the combination of RL with deep learning. At OpenAI, we believe that deep learning generally, and deep reinforcement learning specifically, will play central roles in the development of powerful AI technology. To ensure that AI is safe, we have to come up with safety strategies and algorithms that are compatible with this paradigm. ...
    Downloads: 0 This Week
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  • 12
    Project Malmo

    Project Malmo

    A platform for Artificial Intelligence experimentation on Minecraft

    ...The Malmo platform is a sophisticated AI experimentation platform built on top of Minecraft, and designed to support fundamental research in artificial intelligence. The Project Malmo platform consists of a mod for the Java version, and code that helps artificial intelligence agents sense and act within the Minecraft environment. The two components can run on Windows, Linux, or Mac OS, and researchers can program their agents in any programming language they’re comfortable with.
    Downloads: 3 This Week
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  • 13
    This project provides a framework for testing and comparing different machine learning algorithms (particularly reinforcement learning methods) in different scenarios. Its intended area of application is in research and education.
    Downloads: 0 This Week
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  • 14
    A Python class library of tools for learning agents, including reinforcement learning algorithms, function approximators, and vector quantizations algorithms. (Pronounced "plastic".)
    Downloads: 0 This Week
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  • 15
    General purpose agents using reinforcement learning. Combines radial basis functions, temporal difference learning, planning, uncertainty estimations, and curiosity. Intended to be an out-of-the-box solution for roboticists and game developers.
    Downloads: 0 This Week
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  • 16
    A Python translation of Piqle with Traits for simplified simulation with reinforcement learning agents.
    Downloads: 0 This Week
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